As providers are considering accountable and value based care models, it is critical to strategically think through how to achieve a sustainable business model into the future. This requires actuarial and clinical/provider capabilities to assess the care management and financial levers to help a client through the transition.

A presentation at the Actuarial Research Conference in August 2006 in Montreal. This paper discusses the Basel VaR Value at Risk test of a bank's VaR model. It proposes an alternative, Quality Control of Risk Measures QCRM Hypothesis test. The alternative is more likely to reject an incorrect VaR model.

A 2 page overview of an article for the NAAJ on an actuary's perspective on developments in risk measurement.

It is important to include both risk and return in finding the optimal balance of assets and liabilities for financial institutions. Insurance companies, with their range of sophisticated assets and liabilities, are perhaps the best example of the value of such and approach. Examples in the paper refer to the insurance industry, but parallels to other types of financial institutions are easily drawn. The analysis in the paper shows that a comprehensive approach to risk and return produces some interesting conclusions with respect to asset allocation, active verses passive asset management and the mix and pricing of liabilities.

Over recent years Value at Risk VaR has been accepted in the financial world, and particularly in the banking world, as the yardstick with which to measure portfolio risk. This paper demonstrates the importance of stress testing the model results themselves. Such analyses are useful in order to highlight the underlying model assumptions, the reliability of the assumptions which have been made, and most importantly the effect on the end results if these assumptions were to change. Stress tests are carried out on a fictitious bank to show the sort of useful information and insight they can give.

This paper demonstrates that the building blocks of the insurance process, under similar assumptions, produce identical results to the option-pricing approach in the case of pricing individual loans. We examine the performance of a collective of such building blocks, using portfolio historical performance to endogenously parameterize the default cost function unique to a particular portfolio. Having estimated the appropriate default cost function, we can then specify the reserve requirement for a bank operating such a portfolio.

In contrast to alternative measures to risk, value at risk VaR has important virtues - intelligibility, comparability, and practicality - that make it a potentially valuable tool for strategic decision making and capital management in a wide variety of industries. However, capital-management decisions in most industries - including financial services, such as property/casualty insurance - have time horizons far longer than the one day horizon that prevails in commercial and investment banking, where the use of VaR is now concentrated. For VaR to be usefully applied to long-horizon decisions, it must address three fundamental problems unique to that context: estimation risk, adaptive risk modification, and franchise risk. This paper describes each of these problems, shows how they can be solved, and provides examples applicable to property/casualty insurance.

This paper considers whether Value at Risk VaR satisfies the properties for a coherent risk measure and finds that it does not.It then discusses the implications of this result and suggests that supplementing VaR with another measure, mean excess loss function, can help to solve these problems.

In this paper the authors provide an honest theorem establishing the convergence of the normalized conditional tail expectation [CTE] estimator under importance sampling to a normal distribution. In the process, they also provide a similar result for the value at risk [VaR] estimator under importance sampling, which improves upon an earlier result.

Sometimes, rare things happen and the least expected occurs. Indeed, some events occur once or twice in a lifetime leaving little room to learn from experiences. In financial markets, extreme events, no matter how rare, could have a profound impact on a company or even the whole country. Insurers are also not free from the impact of catastrophic large-scale extreme events. As a result, with pervasive economic and financial revolutions sweeping our world and potential devastative catastrophes, the increasing interest in tail risk management is fuelled by practical issues, including investment downside risk and insurance catastrophe risk. Thus, developing statistical techniques to model extreme investment and insurance losses is certainly a major task for risk managers. the purpose of our paper is to apply moment methods to estimate the joint events such as concurrent extreme investment loss and insurance loss. A novel aspect of this article is that it takes into account the correlation between different assets and insurance lines of business.